The Active Social Engineering Defense (ASED) program aims to develop the core technology to enable the capability to automatically identify, disrupt, and investigate social engineering attacks.

2 天之前 · The Active Social Engineering Defense (ASED) program aims to develop the core technology to enable the capability to automatically identify, disrupt, and investigate social engineering attacks. If successful, the ASED technology will do this by actively detecting attacks, intervening in communications between users and potential attackers, and ...

1 天前 · The description said that the Active Social Engineering Defense (ASED) “will do this by mediating communications between users and potential attackers with bots that actively detect attacks and ...

1 天前 · The scrutiny of this contract, named "ACTIVE SOCIAL ENGINEERING DEFENSE (ASED) LARGE SCALE SOCIAL DECEPTION (LSD)," comes as Musk has spearheaded an effort to cut waste from government agencies ...

A human-in-the-loop system was designed to ensure ongoing adaptation to changes in adversarial tactics, and elimination of false positives, ultimately achieving dramatically improved success rates in the defense against social engineering.

2022年9月12日 · A security method known as Active Social Engineering Defense (ASED) continuously observes staff members looking for anomalous behavior that might point to a social engineering attack. In essence, it is a procedure that aids firms in guarding against social engineering assaults.

View a summary page of this 2018 CONTRACT to THOMSON REUTERS SPECIAL SERVICES LLC from the Department of Defense.

The Active Social Engineering Defense (ASED) program aims to develop the core technology to enable the capability to automatically elicit information from a malicious adversary in order to identify, disrupt, and investigate social engineering attacks.

2022年6月26日 · We argue that employing social engineering active defense (SEAD) will be more effective to countering malicious actors than maintaining the traditional passive defensive strategy. The Offensive Countermeasures (OCM) approach to defense advocates for three categories of countermeasures: annoyance, attribution, and attack.

We describe Panacea, a system that supports nat-ural language processing (NLP) components for active defenses against social engineering attacks. We deploy a pipeline of human language technol-ogy, including Ask and Framing Detection, Named Entity Recognition, Dialogue Engineering, and Sty-lometry.